Field of the Invention
The present invention relates to technology for generating the feature amount of a feature point of an image.
Description of Related Art
In general, a feature point on an image is a point having a unique pixel structure for which a correspondence can be easily found. For example, an angle or an intersection of lines is a feature point. Tracking of a moving body using matching information between feature points of a plurality of images, estimation of a camera position, stereo vision technology, and the like are being widely used. Also, a feature amount is a unique value of each feature point and is used for calculation of the degree of similarity between feature points at the time of matching or for image recognition.
As a feature amount calculation method, a method referred to as scale invariant feature transformation (SIFT) is disclosed in the specification of U.S. Pat. No. 6,711,293. This is a method of making a feature amount of a 128-dimensional vector which represents a distribution of the luminance gradient vectors of pixels in a fixed region of the surroundings of a feature point. The feature amount calculated by this method is strong against rotation of an image and changes in scale and illumination.
In the related method, a feature amount is generated from pixel information of a fixed rectangular region close to a feature point at all times. For this reason, the generated feature amount is weak against movement of a subject, and when a pixel structure in the rectangular region changes, the feature amount of the same feature point greatly changes. In estimation of a camera position or tracking of a moving body, movement of a subject or a change of a viewpoint frequently occurs. For this reason, in the related method, there is a chance of identical feature points of the same subject in a plurality of images not being considered to be the same point due to a slight change of a nearby structure such as a background, and the matching accuracy is degraded.